Stop the war!Остановите войну!
for scientists:
default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDGPTP 2019: Michigan State University, East Lansing, MI, USA
- Wolfgang Banzhaf, Erik D. Goodman, Leigh Sheneman, Leonardo Trujillo, Bill Worzel:
Genetic Programming Theory and Practice XVII [GPTP 2019, Michigan State University, East Lansing, Michigan, USA, May 16-19, 2019]. Springer 2020, ISBN 978-3-030-39957-3 - Austin J. Ferguson, Jose Guadalupe Hernandez, Daniel Junghans, Alexander Lalejini
, Emily L. Dolson, Charles Ofria:
Characterizing the Effects of Random Subsampling on Lexicase Selection. 1-23 - Francisco Fernández de Vega, Gustavo Olague, Francisco Chávez de la O, Daniel Lanza, Wolfgang Banzhaf, Erik D. Goodman:
It Is Time for New Perspectives on How to Fight Bloat in GP. 25-38 - Ivo Gonçalves, Marta Seca, Mauro Castelli:
Explorations of the Semantic Learning Machine Neuroevolution Algorithm: Dynamic Training Data Use, Ensemble Construction Methods, and Deep Learning Perspectives. 39-62 - Ting Hu:
Can Genetic Programming Perform Explainable Machine Learning for Bioinformatics? 63-77 - Lukas Kammerer, Gabriel Kronberger, Bogdan Burlacu, Stephan M. Winkler, Michael Kommenda, Michael Affenzeller:
Symbolic Regression by Exhaustive Search: Reducing the Search Space Using Syntactical Constraints and Efficient Semantic Structure Deduplication. 79-99 - Stephen Kelly, Wolfgang Banzhaf:
Temporal Memory Sharing in Visual Reinforcement Learning. 101-119 - Douglas Kirkpatrick, Arend Hintze:
The Evolution of Representations in Genetic Programming Trees. 121-143 - Arthur K. Kordon, Theresa Kotanchek, Mark E. Kotanchek:
How Competitive Is Genetic Programming in Business Data Science Applications? 145-163 - Anil Kumar Saini, Lee Spector:
Using Modularity Metrics as Design Features to Guide Evolution in Genetic Programming. 165-180 - Joel Lehman:
Evolutionary Computation and AI Safety - Research Problems Impeding Routine and Safe Real-World Application of Evolution. 181-200 - Miguel Nicolau, James McDermott:
Genetic Programming Symbolic Regression: What Is the Prior on the Prediction? 201-225 - Gustavo Olague, Mariana Chan-Ley:
Hands-on Artificial Evolution Through Brain Programming. 227-253 - Edward R. Pantridge, Thomas Helmuth, Lee Spector:
Comparison of Linear Genome Representations for Software Synthesis. 255-274 - Hormoz Shahrzad, Babak Hodjat, Camille Dollé, Andrei Denissov, Simon Lau, Donn Goodhew, Justin Dyer, Risto Miikkulainen:
Enhanced Optimization with Composite Objectives and Novelty Pulsation. 275-293 - Moshe Sipper, Jason H. Moore, Ryan J. Urbanowicz:
New Pathways in Coevolutionary Computation. 295-305 - Andrew N. Sloss, Steven Gustafson:
2019 Evolutionary Algorithms Review. 307-344 - Robert J. Smith, Malcolm I. Heywood:
Evolving a Dota 2 Hero Bot with a Probabilistic Shared Memory Model. 345-366 - David Robert White, Benjamin Fowler, Wolfgang Banzhaf, Earl T. Barr:
Modelling Genetic Programming as a Simple Sampling Algorithm. 367-381 - Yuan Yuan, Wolfgang Banzhaf:
An Evolutionary System for Better Automatic Software Repair. 383-406
a service of 
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
last updated on 2024-07-21 22:15 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
